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Found 8 entries in the Bibliography.
Showing entries from 1 through 8
2022 |
Scintillation due to ionospheric plasma irregularities remains a challenging task for the space science community as it can severely threaten the dynamic systems relying on space-based navigation services. In the present paper, we probe the ionospheric current and plasma irregularity characteristics from a latitudinal arrangement of magnetometers and Global Navigation Satellite System (GNSS) stations from the equator to the far low latitude location over the Indian longitudes, during the severe space weather events of 6–10 ... Vankadara, Ram; Panda, Sampad; Amory-Mazaudier, Christine; Fleury, Rolland; Devanaboyina, Venkata; Pant, Tarun; Jamjareegulgarn, Punyawi; Haq, Mohd; Okoh, Daniel; Seemala, Gopi; Published by: Remote Sensing Published on: jan YEAR: 2022   DOI: 10.3390/rs14030652 space weather; equatorial plasma bubbles; ionospheric irregularity; global navigation satellite system; magnetometer; poleward drift; rate of change of TEC index; scintillations; storm-time electric currents |
This paper investigates the diurnal variations of modelled and observed Vertical Total Electron Content (VTEC) over the African region (40oN to+ 40oS, 25oW to 65oE) obtained from Devanaboyina, Venkata; , others; Published by: Published on: YEAR: 2022   DOI: 10.21203/rs.3.rs-1695991/v1 |
2021 |
Assessment of the predictive capabilities of NIGTEC model over Nigeria during geomagnetic storms The Nigerian Total Electron Content (NIGTEC) is a regional neural network-based model developed by the Nigerian Centre for Atmospheric Research to predict the Total Electron Content (TEC) at any location over Nigeria. The addition of the disturbance storm time (Dst) index as one of NIGTEC s input layer neurons raises a question of its accuracy during geomagnetic storms. In this paper, the capability of NIGTEC in predicting the variability of TEC during geomagnetic storms has been assessed. TEC data predicted by NIGTEC is com ... Amaechi, Paul; Humphrey, Ibifubara; Adewoyin, David; Published by: Geodesy and Geodynamics Published on: nov YEAR: 2021   DOI: 10.1016/j.geog.2021.09.003 geomagnetic storm; global navigation satellite system; Nigerian Total Electron Content (NIGTEC); total electron content |
Recent studies revealed that the long-lasting daytime ionospheric enhancements of Total Electron Content (TEC) were sometimes observed in the Asian sector during the recovery phase of geomagnetic storms (e.g., Lei (J Geophys Res Space Phys 123: 3217–3232, 2018), Li (J Geophys Res Space Phys 125: e2020JA028238, 2020). However, they focused only on the dayside ionosphere, and no dedicated studies have been performed to investigate the nighttime ionospheric behavior during such kinds of storm recovery phases. In this study, w ... Wan, Xin; Xiong, Chao; Gao, Shunzu; Huang, Fuqing; Liu, Yiwen; Aa, Ercha; Yin, Fan; Cai, Hongtao; Published by: Satellite Navigation Published on: nov YEAR: 2021   DOI: 10.1186/s43020-021-00055-x Equatorial plasma irregularity; Geomagneitc storm; Ionospheric response; longitudinal variations; Storm recovery phase |
\textlessp\textgreaterTopside ionospheric background distribution and its seasonal variations over China and its adjacent areas, e.g. 0°-54°N and 70°-140°E, are studied using the in situ electron density (Ne) measurements obtained by the LAP payload on board the ZH-1 (CSES) satellite. Results are as followings:(1) Regularities consistent with results from previous studies are shown on the latitudinal extension, longitudinal distribution, and seasonal variations of the EIA (Equatorial Ionization Anomaly) phenomenon in the ... XiuYing, Wang; DeHe, Yang; ZiHan, Zhou; Jing, C.; Na, Zhou; XuHui, Shen; Published by: Chinese Journal of Geophysics Published on: feb YEAR: 2021   DOI: 10.6038/cjg2021O0152 |
2017 |
of TIMED/GUVI to derive the O/N2 [14], and the data of TIMED/GUVI which are recorded by as the data of Polar BEAR/AIRS and TIMED/GUVI. This method uses the intensity ratio of OI Zhang, Yongchao; Zhu, Jun; Yin, Huan; Zhang, Xiaoxin; Published by: Published on: |
Zhang, Yongchao; Zhu, Jun; Yin, Huan; Zhang, Xiaoxin; Published by: Published on: |
Zhang, Yongchao; Zhu, Jun; Yin, Huan; Zhang, Xiaoxin; Published by: Published on: YEAR: 2017   DOI: 10.1007/978-3-319-49184-410.1007/978-3-319-49184-4_29 |
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